1. Field of the Invention
The present invention relates to the decomposition, annotation, and analysis of processes.
2. Background
Many businesses provide products and/or services according to processes. For instance, processes may be used to generate products, and services may be provided according to processes. The efficiency of such processes is typically of great importance to businesses. More efficient processes enable businesses to provide better service and higher quality products, as well as enabling cost savings and greater profitability. As such, large amounts of attention and resources are allocated by businesses to the control and improvement of processes. One reason for controlling a process is to ensure a predictable outcome, such as a consistent thickness, a consistent cycle time, a consistent quality, etc. Measuring a process helps identify drivers of variation and possibilities for improvement.
Techniques for measuring, analyzing, detecting, and correcting deviations in processes have been devised. The implementation of such techniques is most apparent in manufacturing environments that lend themselves to careful measurement and control techniques. During the early portion of the industrialization of the United States, the scientific method was applied to manufacturing processes in an attempt to find a one best way of performing a particular task. Parameters such as reach, turn, and grasp steps were measured in distance and time. Time and motion studies sought to measure these parameters through disciplined observation, recording of resulting data, and analysis of the data to arrive at an improved arrangement of people, materials, and machines. More recent examples of quality control techniques applied to manufacturing include statistical process control (“SPC”), six sigma, lean manufacturing, and other SPC-based methodologies. These approaches are rooted in measurement, such as the measurement of process outcomes, defect rates, cycle times, means, standard deviations, and/or further metrics.
Techniques have also been devised to help maintain and improve quality in service industries. Such techniques also involve the measurement of service-related metrics, and frequently revolve around training and observation. Unlike manufacturing, service organizations deal with an inherently dynamic and less predictable raw material: interactions with customers. Customers can, and do, make irrational requests, change their minds, make mistakes, and generally behave in ways that never cease to astonish, let alone lend themselves to rigid predictability. When the unpredictability of customers is combined with increasingly sophisticated and varied service offerings, the resulting customer service processes greatly increase measurement complexity.
Accordingly, further ways for improving process quality in manufacturing and service industry environments are desired. For instance, with regard to service industries, techniques for analyzing and improving process quality in interactions with customers are desired.